Abstract
Experimental work across species has demonstrated that spontaneously generated behaviors are robustly coupled to variations in neural activity within the cerebral cortex. Functional magnetic resonance imaging data suggest that temporal correlations in cortical networks vary across distinct behavioral states, providing for the dynamic reorganization of patterned activity. However, these data generally lack the temporal resolution to establish links between cortical signals and the continuously varying fluctuations in spontaneous behavior observed in awake animals. Here, we used wide-field mesoscopic calcium imaging to monitor cortical dynamics in awake mice and developed an approach to quantify rapidly time-varying functional connectivity. We show that spontaneous behaviors are represented by fast changes in both the magnitude and correlational structure of cortical network activity. Combining mesoscopic imaging with simultaneous cellular-resolution two-photon microscopy demonstrated that correlations among neighboring neurons and between local and large-scale networks also encode behavior. Finally, the dynamic functional connectivity of mesoscale signals revealed subnetworks not predicted by traditional anatomical atlas-based parcellation of the cortex. These results provide new insights into how behavioral information is represented across the neocortex and demonstrate an analytical framework for investigating time-varying functional connectivity in neural networks.
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Data availability
The full datasets generated and analyzed in this study are available from the corresponding author on reasonable request. Data for mesoscopic imaging experiments with CCFv3-based parcellation have been deposited on the figshare archive (https://figshare.com/projects/Benisty_Higley_2023/175317).
Code availability
Custom-written MATLAB scripts used in this study are available on GitHub (https://github.com/cardin-higley-lab/Benisty_Higley_2023).
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Acknowledgements
We thank members of the Higley and Cardin laboratories for helpful input throughout all stages of this study. We thank R. Pant and E. Murillo for the generation of adeno-associated virus vectors. We thank the GENIE (Genetically Encoded Neuronal Indicator and Effector) Project for jRCaMP1b plasmids. This work was supported by funding from the National Institutes of Health (MH099045, MH121841 and EY033975 to M.J.H.; EY022951 to J.A.C.; MH113852 to M.J.H. and J.A.C.; EY029581 and GM007205 to D.B.; EY031133 to A.H.M.; EY026878 to the Yale Vision Core Program; EB026936 to G.M. and R.R.C.) and the National Science Foundation (CCF-2217058 to G.M.), an award from the Yale Kavli Institute of Neuroscience (to M.J.H. and R.R.C.), an award from the Swartz Foundation (to H.B.), an award from the Simons Foundation (Simons Foundation Autism Research Initiative award to M.J.H. and J.A.C.), an award from the Smith–Magenis Syndrome Research Foundation (to M.J.H. and J.A.C.) and a Brain & Behavior Research Foundation Young Investigator Grant (to S.L.).
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H.B., R.R.C., G.M., M.C.C., J.A.C. and M.J.H. designed the study. H.B., D.B., R.R.C., G.M. and M.J.H. developed the analytical approach. H.B. carried out all analyses. D.B., A.H.M., S.L. and L.T. collected experimental data. H.B. and M.J.H. wrote the manuscript.
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Benisty, H., Barson, D., Moberly, A.H. et al. Rapid fluctuations in functional connectivity of cortical networks encode spontaneous behavior. Nat Neurosci 27, 148–158 (2024). https://doi.org/10.1038/s41593-023-01498-y
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DOI: https://doi.org/10.1038/s41593-023-01498-y
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